Abstract. This research explores three SPARQL-based techniques to solve Semantic Web tasks that often require similarity measures, such as semantic data integration, ontology mapping, and Semantic Web service matchmaking. Our aim is to see how far it is possible to integrate customized similarity functions (CSF) into SPARQL to achieve good results for these tasks. Our first approach exploits virtual triples calling property functions to establish virtual relations among resources under comparison; the second approach uses extension functions to filter out resources that do not meet the requested similarity criteria; finally, our third technique applies new solution modifiers to post-process a SPARQL solution sequence. The semantics of the three approaches are formally elaborated and discussed. We close the paper with a demonstration of the usefulness of our iSPARQL framework in the context of a data integration and an ontology mapping experiment. 1

Abstract — Much has been written on the promise of Web service discovery and (semi-) automated composition. In this discussion, the value to practitioners of discovering and reusing existing service compositions, captured in workflows, is mostly ignored. This paper presents one solution to workflow discovery. Through a survey with 21 scientists and developers from the my Grid workflow environment, workflow discovery requirements are elicited. Through a user experiment with 13 scientists, an attempt is made to build a gold standard for workflow ranking. Through the design and implementation of a workflow discovery tool, a mechanism for ranking workflow fragments is provided based on graph sub-isomorphism matching. The tool evaluation, drawing on a corpus of 89 public workflows from bioinformatics and the results of the user experiment, finds that the average human ranking can largely be reproduced. I. WEB SERVICES AT WORK IN E-SCIENCE As more scientific resources become available on the World Wide Web, scientists increasingly rely on Web and Grid services for performing in silico (i.e. computerised) experiments. Bioinformatics for example has seen a spectacular rise in the availability of distributed services – the my Grid/Taverna workbench (www.mygrid.org.uk) offers access to over 3000 of these. A popular example of a bioinformatics Web service is BLAST (Basic Local Alignment Search Tool), a service for finding regions of genome sequence similarity (see www.ebi.ac.uk/Tools/webservices). Distributed service composition is difficult, be it manual or automatic. In this light, and to promote cross-disciplinary scientific collaborations, research councils worldwide are building a supporting infrastructure under the banner of e-Science. Exemplar initiatives include the Open Middleware Infrastructure Institute in the United Kingdom (www.omii. ac.uk), D-Grid in Germany (www.d-grid.de) and the

The large amount and heterogeneity of XML documents on the Web require the development of clustering techniques to group together similar documents. Documents can be grouped together according to their content, their structure, and links inside and among documents. For instance, grouping together documents with similar structures has interesting applications in the context of information extraction, of heterogeneous data integration, of personalized content delivery, of access control definition, of web site structural analysis, of comparison of RNA secondary structures. Many approaches have been proposed for evaluating the structural and content similarity between tree-based and vector-based representations of XML documents. Link-based similarity approaches developed for Web data clustering have been adapted for XML documents. This chapter discusses and compares the most relevant similarity measures and their employment for XML document clustering.

The paper provides a conceptual framework for designing and executing business processes using semantic Web services. We envision a world in which a designer defines a “virtual“ Web service as part of a business process, while requiring the system to seek actual Web services that match the specifications of the designer and can be invoked whenever the virtual Web service is activated. Taking a conceptual modeling approach, the relationships between ontology concepts and syntactic Web services are identified. We then propose a generic algorithm for ranking top-K Web services in a decreasing order of their benefit vis-á-vis the semantic Web service. We conclude with an extention of the framework to handle uncertainty as a result of concept mismatch and the desired properties of a schema matching algorithm to support Web service identification.

Abstract. We present a novel method for instance comparison of ontological concepts with regard to personalized content presentation and/or navigation in large information spaces. We assume that comparing properties of documents which users found interesting leads to discovery of information about users ’ interests specifically when considering Semantic Web applications where documents or their parts are represented by ontological concepts. We employ the ontology structure and different similarity metrics for datatype and object properties and investigate reasons behind user interest in the presented content. Moreover, we propose and evaluate an approach to instance similarity computation for a particular user while also considering the user’s individual preferences.

This document describes KMIR, a framework which supports organizations in the successful implementation of Knowledge Management (KM). It follows the holistic approach of a KM introduction by considering technological, organizational and human aspects, as well as organizational culture. The KMIR framework provides recommendations based on Case-Based Reasoning (CBR) and Semantic Web technology. The best practice cases for a successful KM implementation are structured by the use of an ontology.

Abstract. With the envisioned proliferation of Web services available on the WWW and private repositories, new and better support techniques are needed for service discovery and organization to stay manageable. Service classification under hierarchic taxonomies is commonly a key feature for properly organizing service repositories in a rational way, as well as a good foundation for sophisticated retrieval techniques. In this paper, a heuristic approach for the semi-automatic classification of (semantic) Web services is proposed, based on matching new unclassified services to previously classified ones in a given corpus. This hypothesis is validated by an experimental test and the comparison with results achieved by other approaches. 1

Characteristics in the user model can be acquired and maintained in several ways, namely by means of implicit or explicit feedback, observation of user’s actions, log analysis, etc. We use analysis of the content that is presented to a user. We assume that comparing documents and analyzing their common and different aspects can lead to information about user’s interests. We work in the Semantic Web environment where ontologies are used as a mean for content representation. We proposed a recursive method to evaluate similarity of ontological concepts. But computed similarities do not take into account user’s individuality, i.e. the same results are computed for each user. User’s perception of the similarity measure is subjective. Therefore, we extend the method to compute similarity with regard to the user. one in Washington, D.C. and another in London. Figure 1 illustrates this example in the user interface of our personalized

Abstract: Information spreads rapidly across Web sites, Web logs and online forums. This paper describes the research framework of the IDIOM Project (Information Diffusion across Interactive Online Media), 1 which analyzes this process by identifying redundant content elements, mapping them to an ontological knowledge structure, and tracking their temporal and geographic distribution. Linguists define "idiom " as an expression whose meaning is different from the literal meanings of its component words. Similarly, the study of information diffusion promises insights that cannot be inferred from individual network elements. This paper presents underlying technology, initial results, and the future roadmap of investigating information diffusion based on ontological knowledge structures. Similar projects often focus on particular media, or neglect important aspects of the human language. This paper addresses these gaps to reveal fundamental mechanisms of information diffusion across media with distinct interactive characteristics.

Automation in science is increasingly marked by the use of workflow technology. The sharing of workflows through repositories supports the verifiability, reproducibility and extensibility of computational experiments. However, the subsequent discovery of workflows remains a challenge, both from a sociological and technological viewpoint. Based on a survey with participants from 19 laboratories, we investigate current practices in workflow sharing, re-use and discovery amongst life scientists chiefly using the Taverna workflow management system. To address their perceived lack of effective workflow discovery tools, we go on to develop benchmarks for the evaluation of discovery tools, drawing on a series of practical exercises. We demonstrate the value of the benchmarks on two tools: one using graph matching, the other relying on text clustering. key words: